- Title
- Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network
- Creator
- Monjezi, Masoud; Hasanipanah, Mahdi; Khandelwal, Manoj
- Date
- 2013
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/163092
- Identifier
- vital:12777
- Identifier
-
https://doi.org/10.1007/s00521-012-0856-y
- Identifier
- ISBN:0941-0643
- Abstract
- The purpose of this article is to evaluate and predict blast-induced ground vibration at Shur River Dam in Iran using different empirical vibration predictors and artificial neural network (ANN) model. Ground vibration is a seismic wave that spreads out from the blasthole when explosive charge is detonated in a confined manner. Ground vibrations were recorded and monitored in and around the Shur River Dam, Iran, at different vulnerable and strategic locations. A total of 20 blast vibration records were monitored, out of which 16 data sets were used for training of the ANN model as well as determining site constants of various vibration predictors. The rest of the 4 blast vibration data sets were used for the validation and comparison of the result of ANN and different empirical predictors. Performances of the different predictor models were assessed using standard statistical evaluation criteria. Finally, it was found that the ANN model is more accurate as compared to the various empirical models available. As such, a high conformity (R 2 = 0.927) was observed between the measured and predicted peak particle velocity by the developed ANN model. © 2012 Springer-Verlag London Limited.
- Publisher
- Springer Verlag
- Relation
- Neural Computing and Applications Vol. 22, no. 7-8 (2013), p. 1637-1643
- Rights
- Copyright © 2012 Springer-Verlag London Limited.
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0801 Artificial Intelligence and Image Processing; 0906 Electrical and Electronic Engineering; 1702 Cognitive Science; Artificial neural network; Blasting; Ground vibration; Shur River Dam
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